数据可视化：CSV格式，JSON格式

from datetime import datetime
import matplotlib.pyplot as plt
import csv
import numpy as np
with open(‘csv_file\photo.csv‘) as f_obj:
    reader = csv.reader(f_obj)
    dates,heights_1,heights_2 = [],[],[]
    for row in reader:
        try:
            height_1 = float(row[3])#将字符串转换为浮点型
            height_2 = float(row[4])
            # 将字符串‘2018-2-15-13-35-1‘转换为一个表示日期时间的对象
            date = datetime.strptime(row[0], ‘%Y-%m-%d-%H-%M-%S‘)
        except ValueError: #如果有哪一天的数据缺失，打印缺失日期
            print(date,‘missing data.‘)
        else:
            # 将所有高程插入列表
            dates.append(date)
            heights_1.append(height_1)
            heights_2.append(height_2)
fig = plt.figure(figsize=(12,8))
plt.tick_params(axis=‘both‘,labelsize=14)
#为防止x轴标签重叠，让日期型的x轴标签自动展现
fig.autofmt_xdate(rotation=45)
#在同一个窗口中绘制两条折线
x = np.array(dates)
y = np.array(heights_1)
for a,b in zip(x,y):
    #用text()标注,%.nf其中n表示显示小数后面几位，%b表示只标注y
    plt.text(a,b+0.1,‘%.2f‘%b,ha = ‘center‘,va = ‘bottom‘,
            fontsize=8)
    #用annotate()标注，xytext表示偏移距离，%b表示只标注y
    #plt.annotate(‘%s‘%b,xy=(a,b),xytext=(-20,10),
                 #textcoords=‘offset points‘,fontsize=8)
plt.plot(dates,heights_1,linewidth=3,c=‘c‘)
x = np.array(dates)
y = np.array(heights_2)
for a,b in zip(x,y):
    plt.text(a, b + 0.1, ‘%.2f‘ % b, ha=‘center‘, va=‘bottom‘,
             fontsize=8)
plt.plot(dates,heights_2,linewidth=3,c=‘red‘)
#fill_between()接受一个x值系列和两个Y值系列，并填充两个y值系列之间的空间
plt.fill_between(dates,heights_1,heights_2,facecolor=‘greenyellow‘,
                 alpha=0.3)#alpha值代表颜色透明度，默认1
plt.show()

import json
from pygal.style import RotateStyle,LightColorizedStyle
#import pygal.maps.world
import pygal_maps_world.maps
from pygal_maps_world.i18n import COUNTRIES
#定义一个获取两位国别码的函数
def get_country_code(country_name):
    for code,name in COUNTRIES.items():
        if name == country_name:
            return code
    return None
filename = ‘json_file\population_data.json‘
with open(filename) as f:
    #将文件中的字典存储到列表中
    pop_data = json.load(f)
#将每个国家2010年的人口数据加入字典
cc_populations = {}
for pop_dict in pop_data:
    if pop_dict[‘Year‘] == ‘2010‘:
        country_name = pop_dict["Country Name"]
        population = int(float(pop_dict[‘Value‘]))
        code = get_country_code(country_name)
        if code:
            cc_populations[code] = population
            #print(code + ‘:‘ + str(population))
        else:
            print( ‘Error - ‘ + country_name)
#将世界人口数量等级分为三组
cc_pops_1,cc_pops_2,cc_pops_3 = {},{},{}
for cc,pop in cc_populations.items():
    if pop < 10000000:
        cc_pops_1[cc] = pop
    elif pop < 1000000000:
        cc_pops_2[cc] = pop
    else:
        cc_pops_3[cc] = pop
#看看每组有多少个国家
print(len(cc_populations),len(cc_pops_1),len(cc_pops_2),len(cc_pops_3))
wm_style = RotateStyle(‘#336699‘,base_style=LightColorizedStyle)
#wm = pygal.maps.world.World()
wm = pygal_maps_world.maps.World(style=wm_style)
wm.title = ‘World Population in 2010,by Country‘
wm.add(‘0-10m‘,cc_pops_1)
wm.add(‘10m-1bn‘,cc_pops_2)
wm.add(‘>1bn‘,cc_pops_3)
wm.render_to_file(‘images\world_population.svg‘)